Random numbers are pervasively processed within digital electronics. A random number may determine the processing of an application, such as when it the application is associated with gaming. Moreover, a random number may be used as an encryption key for cryptography. Still further, a random number may be used in calculations associated with scientific investigation, such as statistical sampling for a population, etc.
Generally, random numbers are generated by providing a seed value to a random number generator. The random number generator produces a random number in response to the seed value. One area of concern with this process is that the seed value may be discoverable, reproducible, or derivable by an intruder. If an intruder can reproduce the seed value by looking at patterns of random numbers or by using discoverable values to produce the seed value, then the intruder may be able to replicate the random number. Once a random number is successfully reproduced, then the intruder may break keys and other areas of security.
Typical seed values are not truly random. That is, seed values are derived from information that is not random or derived from information that may be subsequently acquired. It is generally assumed that true randomness may only exist in nature; because of the dynamic nature of the environment, there is no given state (e.g., seed) in the environment that can be subsequently reproduced so that a random number may be duplicated.
In fact, randomness is a much sought after concept in digital electronics, because the ability to create true randomness can produce stronger and potentially impenetrable cryptography. However, conventional approaches have failed to use deterministic processing devices (e.g., computers, etc.) to produce true randomness via algorithms which process on those deterministic devices. With conventional approaches, a random number generator is random only if each time the generator is processed it uses a unique and different seed value. Stated another way, if the seeds in two separate devices are the same and the two devices use the same algorithm, then the random numbers generated for the two devices will be the same. Thus, true randomness remains an elusive concept in the digital arts because of the deterministic nature of processing devices and the deterministic information used in algorithms that execute on the processing devices.
Therefore, an improved random number generator and improved random number generation techniques are desirable.